Error bars using plot_pandas_GUI()

You can try this notebook live by lauching it in Binder.This can take a while to launch, be patient. Binder.

First we import pandas, pandas_GUI plus numpy, and create some data. In this case a noisy sine wave.

Default plot of the data set

This is the plot made using the default settings of plot_pandas_GUI(). See step-by-step example.

Figure 1: This should display a live plotly plot that can be zoomed and show point values upon hovering. If you do not see a live plot the notebook is not running or trusted. Click on the 'Not Trusted' button in the Jupyter menu bar to trust the notebook.

Displaying Error Bars

Rather than using the default plot options, before adding a trace to the plot you can customize how it will be displayed.

An image of the expanded Y error bars section is shown below.

Y error bars section of tab 1

The choices in the Error Type dropdown are:

The plots below show views with the different error bar options.

Percent error bars

Figure 2: Example of percent error bars. In this case they are 5% of $\left |{Amplitude} \right |$.

Constant error bars

Figure 3: Examples of the constant error bars ($\pm5$).

Error bars from data

We start by adding a column of random numbers with a standard deviation of 10 to our dataframe. Then choose that column as our errors.

Figure 4: Example of error bars using the data choice. It may be easier to see the variation if you zoom in on a region.

Learn More

In addition to trying it below if this is a live notebook, you can look at the other examples listed in the Pandas GUI website.

Try It

If you are running this notebook live in binder you can try it here by running the first cell to import the tools and data. Then run the cell below to create the GUI. Note: You may want to expand the collapsed instructions to learn more about each tab.